I have been working in the domain of eye tracking and gaze pattern modeling since 2015, which started as a master level lab project. I continued my work in this field with my Ph.D. My doctoral thesis. The topic fit my background in psychology and cognitive science, thus bringing a better understanding of the cognitive strategies of experts and not solely quantifying gaze behavior differences. From my doctoral research, I have gained experience in applying of deep learning and other machine learning methods to model gaze behavior and developing attention-aware intelligent systems. This work has contributed 13 publications to eye tracking research and has received one best paper award for a fast scanpath analysis approach for multiple domains. I finished my Ph.D. in October 2020 on the topic of gaze based features for data-driven expertise recognition in dental medical image inspection. Currently, I am working as a Post Doc at the Zeiss Vision Science Lab, which is also a part of the University Clinic in Tübingen. My current work investigates ways to have a lean communication system with user and medical AI systems. With gaze as one part of a developing multimodal interface, I am eager to continue my work on the topic of visual search modeling and I feel it promotes the interdisciplinary context of machine learning. I aim to understand how machine learning and AI can transform disciplines. For instance, with AI becoming extremely pervasive in medical professions, research into how professionals inspect medical images with AI decision support systems as well as users interacting with AI controlled prosthetics contributes to our understanding of interaction and feelings of trust with AI. This research can also maintain up-to-date understanding of computer-assisted learning, intelligent systems and feedback to user.